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open-standards/aac/aac-rs/data/asr/index.json
Transaction Science ace56fe36f fix(aac listener): timers from the press, no mic on a hidden page; measured slots only 
- Listening's timers (30 s for words, 90 s in all) run from the press, so
  a permission prompt nobody answers, or audio that never starts, ends it
  too, and no wait holds the sentence helper; a page already hidden does
  not open the microphone, and one hidden while the browser asked lets it
  go.
- A finish that fails drops the worker, as a failed run does; a failed
  first-run check lets the model go (it kept 1.3 GB loaded).
- Test hooks: shorter timers, the app counted as speaking, the worker's
  events counted, a failed run on request.
- Every locale of a language uses the prompt slot that was measured for it.
  FLEURS has one accent per language, so the model's en-GB, es-US, pt-PT
  and fr-CA slots cannot be measured, and are not used.
- eval/score.py counts the clips the end-of-speech rule cut at a pause
  against the run with no end at all (--no-end), the one method used for
  the notes and the README: with 1 s, Hindi 3 and Portuguese 1; with
  500 ms, 43 of 400 (Vietnamese 16, Hindi 5, Portuguese 5, Italian 4,
  German 3).

Co-Authored-By: Claude Opus 5.5 <[email protected]>
2026-10-01 23:11:58 -04:00

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{
"schema": "aac-asr-index/1",
"generated": "2026-10-01",
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"what": "speech recognition",
"attribution": "NVIDIA Nemotron 3.5 ASR Streaming 0.6B by NVIDIA, in soniqo's fp16 ONNX export, its graphs edited to run on WebGPU",
"licence": "OpenMDW-1.1",
"licence_url": "https://openmdw.ai/license/1-1/",
"licence_file": "licences/OpenMDW-1.1.2ab44b683654.txt"
},
{
"what": "finding speech",
"attribution": "Silero VAD v6.2.3 by the Silero Team, its graph edited to run on WebGPU",
"licence": "MIT",
"licence_url": "https://github.com/snakers4/silero-vad/blob/v6.2.3/LICENSE",
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},
"languages": {
"am": {
"status": "not-yet",
"name": "Amharic",
"note": "The speech model was not trained to write Amharic down."
},
"ar": {
"status": "ready",
"name": "Arabic",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 7,
"measure": "wer",
"published": 12.55,
"measured": 8.4,
"source": "ours (what decides): the first 25 FLEURS test clips of ar_eg (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 8 words in 100 came out wrong (NVIDIA's own test: about 13)."
},
"bn": {
"status": "not-yet",
"name": "Bengali",
"note": "The speech model was not trained to write Bengali down."
},
"cs": {
"status": "not-yet",
"name": "Czech",
"slot": 22,
"measure": "wer",
"published": 22.41,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 22 words in 100 came out wrong: too many to rely on yet."
},
"da": {
"status": "not-yet",
"name": "Danish",
"slot": 25,
"measure": "wer",
"published": 30.0,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 30 words in 100 came out wrong: too many to rely on yet."
},
"de": {
"status": "ready",
"name": "German",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 9,
"measure": "wer",
"published": 8.83,
"measured": 12.91,
"source": "ours (what decides): the first 25 FLEURS test clips of de_de (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 13 words in 100 came out wrong (NVIDIA's own test: about 9)."
},
"el": {
"status": "not-yet",
"name": "Greek",
"note": "NVIDIA trained the speech model on it only as a start for more training; it does not write Greek down well yet."
},
"en": {
"status": "ready",
"name": "English",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 0,
"measure": "wer",
"published": 8.27,
"measured": 9.78,
"source": "ours (what decides): the first 25 FLEURS test clips of en_us (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 10 words in 100 came out wrong (NVIDIA's own test: about 8)."
},
"es": {
"status": "ready",
"name": "Spanish",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 2,
"measure": "wer",
"published": 4.39,
"measured": 4.47,
"source": "ours (what decides): the first 25 FLEURS test clips of es_419 (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 4 words in 100 came out wrong (NVIDIA's own test: about 4)."
},
"fa": {
"status": "not-yet",
"name": "Persian",
"note": "The speech model was not trained to write Persian down."
},
"fi": {
"status": "not-yet",
"name": "Finnish",
"slot": 26,
"measure": "wer",
"published": 20.05,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 20 words in 100 came out wrong: too many to rely on yet."
},
"fr": {
"status": "ready",
"name": "French",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 8,
"measure": "wer",
"published": 9.79,
"measured": 11.67,
"source": "ours (what decides): the first 25 FLEURS test clips of fr_fr (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 12 words in 100 came out wrong (NVIDIA's own test: about 10)."
},
"gu": {
"status": "not-yet",
"name": "Gujarati",
"note": "The speech model was not trained to write Gujarati down."
},
"ha": {
"status": "not-yet",
"name": "Hausa",
"note": "The speech model was not trained to write Hausa down."
},
"he": {
"status": "not-yet",
"name": "Hebrew",
"note": "NVIDIA trained the speech model on it only as a start for more training; it does not write Hebrew down well yet."
},
"hi": {
"status": "not-yet",
"name": "Hindi",
"slot": 6,
"measure": "wer",
"published": 7.41,
"measured": 17.51,
"source": "ours (what decides): the first 25 FLEURS test clips of hi_in (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 18 words in 100 came out wrong: too many to rely on yet, partly because it stopped listening at a long pause between sentences (3 of 25)."
},
"hu": {
"status": "not-yet",
"name": "Hungarian",
"slot": 23,
"measure": "wer",
"published": 30.92,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 31 words in 100 came out wrong: too many to rely on yet."
},
"id": {
"status": "not-yet",
"name": "Indonesian",
"note": "The speech model was not trained to write Indonesian down."
},
"it": {
"status": "ready",
"name": "Italian",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 15,
"measure": "wer",
"published": 4.83,
"measured": 6.89,
"source": "ours (what decides): the first 25 FLEURS test clips of it_it (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 7 words in 100 came out wrong (NVIDIA's own test: about 5)."
},
"ja": {
"status": "ready",
"name": "Japanese",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 10,
"measure": "cer",
"published": 12.22,
"measured": 14.61,
"source": "ours (what decides): the first 25 FLEURS test clips of ja_jp (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 15 characters in 100 came out wrong (NVIDIA's own test: about 12)."
},
"kn": {
"status": "not-yet",
"name": "Kannada",
"note": "The speech model was not trained to write Kannada down."
},
"ko": {
"status": "ready",
"name": "Korean",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 14,
"measure": "cer",
"published": 7.27,
"measured": 10.74,
"source": "ours (what decides): the first 25 FLEURS test clips of ko_kr (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 11 characters in 100 came out wrong (NVIDIA's own test: about 7)."
},
"ml": {
"status": "not-yet",
"name": "Malayalam",
"note": "The speech model was not trained to write Malayalam down."
},
"mr": {
"status": "not-yet",
"name": "Marathi",
"note": "The speech model was not trained to write Marathi down."
},
"ms": {
"status": "not-yet",
"name": "Malay",
"note": "The speech model was not trained to write Malay down."
},
"nb": {
"status": "not-yet",
"name": "Norwegian",
"slot": 103,
"measure": "wer",
"published": 18.9,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 19 words in 100 came out wrong: too many to rely on yet."
},
"nl": {
"status": "not-yet",
"name": "Dutch",
"slot": 16,
"measure": "wer",
"published": 12.17,
"measured": 16.23,
"source": "ours (what decides): the first 25 FLEURS test clips of nl_nl (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 16 words in 100 came out wrong: too many to rely on yet."
},
"pa": {
"status": "not-yet",
"name": "Punjabi",
"note": "The speech model was not trained to write Punjabi down."
},
"pl": {
"status": "not-yet",
"name": "Polish",
"slot": 17,
"measure": "wer",
"published": 17.48,
"measured": 17.36,
"source": "ours (what decides): the first 25 FLEURS test clips of pl_pl (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 17 words in 100 came out wrong: too many to rely on yet."
},
"pt": {
"status": "ready",
"name": "Portuguese",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 12,
"measure": "wer",
"published": 5.81,
"measured": 11.43,
"source": "ours (what decides): the first 25 FLEURS test clips of pt_br (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 11 words in 100 came out wrong (NVIDIA's own test: about 6)."
},
"ro": {
"status": "not-yet",
"name": "Romanian",
"slot": 20,
"measure": "wer",
"published": 29.04,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 29 words in 100 came out wrong: too many to rely on yet."
},
"ru": {
"status": "ready",
"name": "Russian",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 11,
"measure": "wer",
"published": 9.87,
"measured": 14.32,
"source": "ours (what decides): the first 25 FLEURS test clips of ru_ru (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 14 words in 100 came out wrong (NVIDIA's own test: about 10)."
},
"sv": {
"status": "not-yet",
"name": "Swedish",
"slot": 24,
"measure": "wer",
"published": 23.63,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 24 words in 100 came out wrong: too many to rely on yet."
},
"sw": {
"status": "not-yet",
"name": "Swahili",
"note": "The speech model was not trained to write Swahili down."
},
"ta": {
"status": "not-yet",
"name": "Tamil",
"note": "The speech model was not trained to write Tamil down."
},
"te": {
"status": "not-yet",
"name": "Telugu",
"note": "The speech model was not trained to write Telugu down."
},
"th": {
"status": "not-yet",
"name": "Thai",
"note": "NVIDIA trained the speech model on it only as a start for more training; it does not write Thai down well yet."
},
"tl": {
"status": "not-yet",
"name": "Filipino",
"note": "The speech model was not trained to write Filipino down."
},
"tr": {
"status": "not-yet",
"name": "Turkish",
"slot": 18,
"measure": "wer",
"published": 12.05,
"measured": 16.19,
"source": "ours (what decides): the first 25 FLEURS test clips of tr_tr (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 16 words in 100 came out wrong: too many to rely on yet."
},
"uk": {
"status": "ready",
"name": "Ukrainian",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 19,
"measure": "wer",
"published": 14.55,
"measured": 13.8,
"source": "ours (what decides): the first 25 FLEURS test clips of uk_ua (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 14 words in 100 came out wrong (NVIDIA's own test: about 15)."
},
"ur": {
"status": "not-yet",
"name": "Urdu",
"note": "The speech model was not trained to write Urdu down."
},
"vi": {
"status": "ready",
"name": "Vietnamese",
"model": "nemotron-3.5-asr-streaming-0.6b",
"slot": 33,
"measure": "wer",
"published": 12.29,
"measured": 14.11,
"source": "ours (what decides): the first 25 FLEURS test clips of vi_vn (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In our test of 25 read-aloud passages, on this app, about 14 words in 100 came out wrong (NVIDIA's own test: about 12)."
},
"yo": {
"status": "not-yet",
"name": "Yoruba",
"note": "The speech model was not trained to write Yoruba down."
},
"zh": {
"status": "not-yet",
"name": "Chinese",
"slot": 4,
"measure": "cer",
"published": 20.03,
"source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
"note": "In NVIDIA's own test on read speech, about 20 characters in 100 came out wrong: too many to rely on yet."
},
"zu": {
"status": "not-yet",
"name": "Zulu",
"note": "The speech model was not trained to write Zulu down."
}
}
}
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